Rasit Onur Topaloglu

Trapped-ion (TI) quantum computer is one of the forerunner quantum technologies. However, TI systems can have a limited number of qubits in a single trap. Execution of meaningful quantum algorithms requires a multiple trap system. In such systems, the computation may frequently involve ions from two different traps for which the qubits must be co-located in the same trap, hence one of the ions needs to be shuttled (moved) between traps, increasing the vibrational energy, degrading fidelity, and increasing the program execution time. The choice of initial mapping influences the number of shuttles. The existing Greedy policy counts the number of gates occurring between each pair of qubits and assigns edge weight. The qubits with high edge weights are placed close to each other. However, it neglects the stage of the program at which the gate is occurring. Intuitively, the contribution of the late-occurring gates to the initial mapping reduces since the ions might have already shuttled to a different trap to satisfy other gate operations. In this paper, we target this gap and propose a new policy especially for programs with considerable depth and high number of qubits (valid for practical-scale quantum programs). Our policy is program adaptive and prioritizes the gates re-occurring at the initial stages of the program over late occurring gates. Our technique achieves an average reduction of 9% shuttles/program (with 21.3% at best) for 120 random circuits and enhances the program fidelity up to 3.3X (1.41X on average).

Trapped-ion systems can have a limited number of ions (qubits) in a single trap. Increasing the qubit count to run meaningful quantum algorithms would require multiple traps where ions need to shuttle between traps to communicate. The existing compiler has several limitations which result in a high number of shuttle operations and degraded fidelity. In this paper, we target this gap and propose compiler optimizations to reduce the number of shuttles. Our technique achieves a maximum reduction of $51.17\%$ in shuttles (average $\approx 33\%$) tested over $125$ circuits. Furthermore, the improved compilation enhances the program fidelity up to $22.68$X with a modest increase in the compilation time.

Trapped-ion (TI) quantum bits are a front-runner technology for quantum computing. TI systems with multiple interconnected traps can overcome the hardware connectivity issue inherent in superconducting qubits and can solve practical problems at scale. With a sufficient number of qubits on the horizon, the multi-programming model for Quantum Computers (QC) has been proposed where multiple users share the same QC for their computing. Multi-programming is enticing for quantum cloud providers as it can maximize device utilization, throughput, and profit for clouds. Users can also benefit from the short wait queue. However, shared access to quantum computers can create new security issues. This paper presents one such vulnerability in shared TI systems that require shuttle operations for communication among traps. Repeated shuttle operations increase quantum bit energy and degrade the reliability of computations (fidelity). We show adversarial program design approaches requiring numerous shuttles. We propose a random and systematic methodology for adversary program generation. Our analysis shows shuttle-exploiting attacks can substantially degrade the fidelities of victim programs by 2X to 63X. Finally, we present several countermeasures such as adopting a hybrid initial mapping policy, padding victim programs with dummy qubits, and capping maximum shuttles.